Senior Analytics Engineer

Your mission As a member of our Data team, you'll take full ownership of the systems that turn raw data into decisions—for our product, our internal teams, our customers, and our investors. You won't just maintain dashboards; you'll own the pipeline end to end, from ingestion to the numbers people actually act on. In your first few months, you might: Take ownership of our dbt pipeline, improving our data models so they're reliable, well-tested, and easy to build on. Maintain and extend our Looker setup, and ship new dashboards and reports that customers and other stakeholders depend on. Strengthen our data pipeline from Postgres to BigQuery, and build custom Python scripts to automate the flows that keep our warehouse fresh. Integrate our data warehouse with external tools like Salesforce or ActiveCampaign, so the right data reaches the teams that need it. How We Build: Our Engineering Culture We believe in a calm, collaborative, and productive engineering environment. We trust our people and give them the autonomy to do their best work. Our approach includes: Ownership Over Handoffs: On a small data team, you own your work from ingestion to dashboard. We trust you to make decisions and run with them. Quality by Default: We treat our data models like production code—tested, version-controlled, and documented—so the numbers we serve are ones we can stand behind. DevOps Mindset: We automate the boring parts. Pipelines, syncs, and checks are powered by third-party tools or GitHub Actions so the team can focus on the work that needs a human. Collaboration & Transparency: We value open discussion, constructive reviews, and a culture where the best idea wins, regardless of who it comes from. AI-Native by Default: We work heavily with Claude Code and other AI tools, and they're a core part of how we build—from writing models and scripts to debugging pipelines and exploring data. We expect everyone on the team to use them fluently and keep getting better at it. Your profile We're looking for an experienced data practitioner who likes owning the full stack of an analytics platform. You'll be a great fit if you have: Significant professional experience building and maintaining data models with dbt and writing advanced SQL . Solid Python skills for data syncing, automation, and general scripting. Hands-on experience with a cloud data warehouse such as BigQuery , and comfort working with source databases like Postgres . Experience building dashboards and serving data to non-technical stakeholders (a strong command of Looker is a big plus). Strong, hands-on familiarity with AI coding tools—especially Claude Code —and a habit of using them as part of your daily workflow. A pragmatic approach to problem-solving and a high sense of ownership, feeling comfortable driving projects independently. Excellent communication skills in English. Bonus Points For (Nice-to-Haves): Experience with reverse ETL or integrating a data warehouse with tools like ActiveCampaign